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Python Anaconda Tutorial: Everything You Need to Know

UserAlexander Anderson time01 August,2022

For scientific computing (data science, machine learning applications, large-scale data processing, predictive analytics, etc.), Anaconda is a distribution of the Python and R programming languages that seek to streamline package management and deployment. Data-science courses are included in the distributions that are compatible with Windows, Linux, and macOS. It is created and maintained by Anaconda, Inc., a company that was established in 2012 by Peter Wang and Travis Oliphant. It is also referred to as Anaconda Distribution or Anaconda Individual Edition as an Anaconda, Inc. product; the firm also produces Anaconda Team Edition and Anaconda Enterprise Edition, all of which are paid options.

Anaconda assists in streamlining deployment and package management. The large range of tools included with Anaconda makes it simple to gather data from numerous sources using various machine learning and AI methods. It assists in setting up an environment that is simple to administer and allows for the quick deployment of any project.

The package management system conda is in charge of managing package versions in Anaconda. This package manager turned out to be valuable on its own and for uses other than Python, so it was spun out as a distinct open-source package. Miniconda is a boot-strapped, scaled-down variation of Anaconda that only contains conda, Python, the programmes they depend on, and a select few more packages.

a) How is Anaconda related to Python?

Python and Anaconda are related in that Anaconda is a platform for scientific computing and data processing built on Python. It has a tonne of third-party libraries that are quite helpful. It is much simpler to install Anaconda than normal Python because doing so immediately instals Python as well as some frequently used libraries including Numpy, Pandas, Scrip, and Matplotlib. You must use pip to install each library individually if you choose to install Python from python.org rather than Anaconda. Direct installation of Anaconda is strongly advised because it is painful and you must take compatibility into account.

Python and R's distribution make up the entirety of Anaconda. It constantly strives to deliver all you need for data science "out of the box" in terms of Python.

It contains the following:

  • The basic syntax of Python
  • Numerous Python "packages" (libraries)
  • Jupyter with Spyder (IDE/editor similar to PyCharm)
  • For upgrading Anaconda and packages, utilise conda, Anaconda's native package manager.

1. Difficulty in installing a package in Anaconda

A package management service for both public and private package repositories, Anaconda.org, offers packages that are not accessible through conda install. Like Anaconda and Miniconda, Anaconda.org is a product of Anaconda.

Installing a package from Anaconda.org involves:

  • Go to http://anaconda.org in a browser.
  • Enter bottleneck in the top-left box labelled "Search Packages" to find the bottleneck package.
  • Locate the desired bundle and click it to access the detail page.
  • The name of the channel is shown on the detail page. The "pandas" channel is used in this instance.

Use the conda install command to install the package now that you are aware of the channel name. Run this command in a terminal window or an Anaconda Prompt:

If you have difficulty in installing anaconda package, Open an Anaconda Prompt (terminal on Linux or macOS) and follow these instructions:

  • Enter the command: conda install package-name=2.3.4
  • To specify only a major version, run: conda install package-name=2
  • These instructions install themselves into the active environment. Run: to set up in a named environment: conda install package-name=2.3.4 -n some-environment
  • Conda uses the version of Python that is installed in the current or named environment if the package is version-specific. Consult the Conda FAQ and Conda Troubleshooting for further information on versions, dependencies, and channels.

Installing packages on a non-networked (air-gapped) computer

  • To directly install a conda package from your local computer, run: conda install /package-path/package-filename.tar.bz2
  • Conda installs packages into the anaconda/pkgs directory.
  • To install a .tar file containing many conda packages, run the following command: conda install /packages-path/packages-filename.tar
  • Try using an absolute path name rather than a relative path name if conda is unable to locate the file.

b) How tothe check python anaconda version

Run python -V or python —version to see your Python version in Anaconda. Conda -V or conda —version can be used to determine your conda version. Run conda list anaconda to see the version of Anaconda. $ Run conda list python -f to see the Python version installed on your system.

Run the command conda list in your Terminal window or Anaconda Prompt to verify your installation. When an installation is successful, a list of installed packages is displayed.

Given that the anaconda is a very sophisticated creature, the task might not seem simple at first. First off, Anaconda is the name of the distribution, which is also the name of a meta-package (a package of packages) that is entirely contained within the distribution.

As a result, all you have to do to determine your Anaconda version after installatoion is look at the meta-package version. Conda, the package manager for Anaconda, can be used for this:

conda list anaconda$

Due to the $ and the end, this command will only return the package with the name "anaconda" (yes, it really is a regular expression):

You can see that above is the most recent version (at time of writing, 5.1.0). Conda list can be used to check the installed version of any distribution package.

Updating Anaconda

It is preferable to update the package management before updating the distribution if I need to:

  • Conda update conda

And then update the meta-package

  • Conda update anaconda

The entire Anaconda distribution will be updated. You'll have the most recent Anaconda distribution as soon as the "anaconda" meta-package is updated.

You can choose "update everything" if you wish to update everything, including additional software like anaconda-navigator and related programs as well as Python projects:

  • Update conda —all

Please be aware that by doing this step, all packages will be updated to the most recent version, which may differ from the version provided with the anaconda metapackage. So, to sum up:

Regardless of what is in the anaconda meta package, if you want the most recent version of a package,

  • update conda  --all

Additional Anaconda Information

Use the following command to find out which version of Python Anaconda is running on, as well as the platform it is running on, base paths for the environment, and packages.

  • Conda info

c) List of packages installed in Anaconda

All packageslisted below are in the package repository and can be installed with the command conda install PACKAGENAME. To view the packages that are offered for each operating system, each architecture, and each version of Python (3.8, 3.7, or 3.9), click one of the links below.

On the Intel and AMD x86, x86-64 CPU, AWS Graviton 2 / ARM 64, IBM Z and IBM Power CPU architectures, Anaconda is available for 64 and 32 bit Windows, macOS (Intel x86 and Apple M1), and 64 Linux.

Every time a new package is added to the Anaconda package repository, an RSS feed is updated.

 Python 3.9Python 3.8Python 3.7
64-bit Windows64-bit Windows, Py3.964-bit Windows, Py3.8
64-bit Windows, Py3.7 
32-bit Windows32-bit Windows, Py3.932-bit Windows, Py3.8
32-bit Windows, Py3.7 
64-bit macOS Intel x86macOS Intel x86, Py3.9macOS Intel x86, Py3.8
macOS Intel x86, Py3.7 
64-bit macOS Apple M1macOS Apple M1, Py3.9macOS Apple M1, Py3.8
Not supported 
64-bit Linux64-bit Linux, Py3.964-bit Linux, Py3.8
64-bit Linux, Py3.7 
64-bit Linux Graviton2 ARM64Linux on ARM64, Py3.9Linux on ARM64, Py3.8Linux on ARM64, Py3.7
64-bit Linux on IBM ZLinux on IBM Z, Py3.9Linux on IBM Z, Py3.8Linux on IBM Z, Py3.7
64-bit Linux on IBM Power CPUsLinux on IBM Power, Py3.9Linux on IBM Power, Py3.8Linux on IBM Power, Py3.7

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